A local binary patterns/variance operator based on guided filtering for seismic fault detection

Abstract Aiming at suppressing noise interference, improving the fault detection ability of seismic data, fully excavating the effective information in seismic data, and further improving the accuracy of fault detection, this study proposes a seismic fault detection method that combines the local bi...

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Autores principales:	Renfei Tian, Xue Lei, Min Ouyang
Formato:	article
Lenguaje:	EN
Publicado:	Springer 2021
Materias:	Edge detection Fault detection Guided filtering LBP/VAR Science Q Technology T
Acceso en línea:	https://doaj.org/article/3c2e90c6cd1b4d7ca5ef019a07fb69e9
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id	oai:doaj.org-article:3c2e90c6cd1b4d7ca5ef019a07fb69e9
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spelling	oai:doaj.org-article:3c2e90c6cd1b4d7ca5ef019a07fb69e92021-11-21T12:12:31ZA local binary patterns/variance operator based on guided filtering for seismic fault detection10.1007/s42452-021-04866-02523-39632523-3971https://doaj.org/article/3c2e90c6cd1b4d7ca5ef019a07fb69e92021-11-01T00:00:00Zhttps://doi.org/10.1007/s42452-021-04866-0https://doaj.org/toc/2523-3963https://doaj.org/toc/2523-3971Abstract Aiming at suppressing noise interference, improving the fault detection ability of seismic data, fully excavating the effective information in seismic data, and further improving the accuracy of fault detection, this study proposes a seismic fault detection method that combines the local binary pattern/variance (LBP/VAR) operator with guided filtering. The proposed method combines the advantages of LBP/VAR and guided filtering to remove noise from seismic data, and can simultaneously smooth the data and preserve linear features. When compared with several existing methods (coherent operator, LBP/VAR operator, LBP/VAR operator based on median filtering, and Canny operator based on guided filtering), the proposed method exhibits a better SNR, a better ability to identify small faults, and robustness to noise. This novel algorithm can control the balance between noise attenuation and effective signal preservation as well as effectively detect faults in seismic data. Therefore, the proposed method effectively improves the fault identification accuracy, facilitates the gas-bearing analysis of the structure, provides guidance for the actual well location deployment of the project, and has important practical significance for oil and gas exploration and development.Renfei TianXue LeiMin OuyangSpringerarticleEdge detectionFault detectionGuided filteringLBP/VARScienceQTechnologyTENSN Applied Sciences, Vol 3, Iss 12, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Edge detection Fault detection Guided filtering LBP/VAR Science Q Technology T
spellingShingle	Edge detection Fault detection Guided filtering LBP/VAR Science Q Technology T Renfei Tian Xue Lei Min Ouyang A local binary patterns/variance operator based on guided filtering for seismic fault detection
description	Abstract Aiming at suppressing noise interference, improving the fault detection ability of seismic data, fully excavating the effective information in seismic data, and further improving the accuracy of fault detection, this study proposes a seismic fault detection method that combines the local binary pattern/variance (LBP/VAR) operator with guided filtering. The proposed method combines the advantages of LBP/VAR and guided filtering to remove noise from seismic data, and can simultaneously smooth the data and preserve linear features. When compared with several existing methods (coherent operator, LBP/VAR operator, LBP/VAR operator based on median filtering, and Canny operator based on guided filtering), the proposed method exhibits a better SNR, a better ability to identify small faults, and robustness to noise. This novel algorithm can control the balance between noise attenuation and effective signal preservation as well as effectively detect faults in seismic data. Therefore, the proposed method effectively improves the fault identification accuracy, facilitates the gas-bearing analysis of the structure, provides guidance for the actual well location deployment of the project, and has important practical significance for oil and gas exploration and development.
format	article
author	Renfei Tian Xue Lei Min Ouyang
author_facet	Renfei Tian Xue Lei Min Ouyang
author_sort	Renfei Tian
title	A local binary patterns/variance operator based on guided filtering for seismic fault detection
title_short	A local binary patterns/variance operator based on guided filtering for seismic fault detection
title_full	A local binary patterns/variance operator based on guided filtering for seismic fault detection
title_fullStr	A local binary patterns/variance operator based on guided filtering for seismic fault detection
title_full_unstemmed	A local binary patterns/variance operator based on guided filtering for seismic fault detection
title_sort	local binary patterns/variance operator based on guided filtering for seismic fault detection
publisher	Springer
publishDate	2021
url	https://doaj.org/article/3c2e90c6cd1b4d7ca5ef019a07fb69e9
work_keys_str_mv	AT renfeitian alocalbinarypatternsvarianceoperatorbasedonguidedfilteringforseismicfaultdetection AT xuelei alocalbinarypatternsvarianceoperatorbasedonguidedfilteringforseismicfaultdetection AT minouyang alocalbinarypatternsvarianceoperatorbasedonguidedfilteringforseismicfaultdetection AT renfeitian localbinarypatternsvarianceoperatorbasedonguidedfilteringforseismicfaultdetection AT xuelei localbinarypatternsvarianceoperatorbasedonguidedfilteringforseismicfaultdetection AT minouyang localbinarypatternsvarianceoperatorbasedonguidedfilteringforseismicfaultdetection
_version_	1718419116974407680

A local binary patterns/variance operator based on guided filtering for seismic fault detection

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